Let $\{T_i\}_{i=1}^d$ a set of i.i.d random variables that are symmetric about the origin. Also,let $T = \frac{1}{d} \sum_{i=1}^d T_i$. Then, for every $k=0,1,\dots$, we have $$\mathbb E[T^{2k}] = \frac{1}{d^{2k}}\sum_{i_1=1}^d\cdots \sum_{i_{2k}=1}^d \mathbb E[T_{i_1}\cdots T_{i_{i_{2k}}}]\tag{1}$$
According to @user170231 comment, $(1)$ looks like a multinational expansion. In addition, for a symmetric distribution whose odd-order moments exist, we have that the odd-order moments are equal to zero (see here). Maybe another useful post is this which I found complicated to use it.
Here I summarize what I need to understand after @Robert Israel's answer. How
$$\mathbb E[T^{2k}] = \sum_{j_1+j_2+\cdots+j_d=2k; \\ j_1, j_2, \cdots, j_d \geq 0} {2k \choose j_1,j_2,\ldots, j_{d}} \mathbb E[T_{1}^{j_1}] \ldots \mathbb E[T_d^{j_{d}}]$$ is reduced to the even powers of $T_{i}$, which probably reveals the term $1/d^{2k}$ and how we get $\mathbb E[T_{1}^{j_1}\cdots T_{d}^{l_{d}}]= \mathbb E[T_{i_1}\cdots T_{i_{2k}}]$.
Any help is highly appreciated.
The equation is from here proof of lemma 8.